Investigation of Tunnel Stability by Land Characteristic Curve Method Using Learning Machine Algorithm

Document Type : Original Article

Authors

1 BSc, MSc, Geotechnical Engineer, Tehran, Iran

2 M.Sc., Grad., Sahel Omid Iranian Consulting Engineers, Tehran, Iran.

3 M.Sc., Grad., Youth and Elite Research Club of Islamic Azad University, Kermanshah Branch, Iran.

4 M. Sc.,Grad., Faculty of Engineering, Islamic Azad University, Tehran Branch, Tehran, Iran

Abstract

Due to the increasing development of underground spaces, assessment of sustainability and determination of rock mass behavior is one of the important issues of underground space for safety and optimization of the project. In recent years, critical strain has been considered as the most important indicator for assessing the stability and squeezing of the tunnel. There are currently several methods for determining the critical strain of the essence of rock mass. The critical strain parameter is an indicator that allows the degree of squeezing potential to be measured in terms of quantity. It is referred to as the strain level around the tunnel, which further causes instability and squeezing problems that are likely to occur. Also, the critical strain rate is very useful in evaluating the tunnel stability using the land-characteristic charts. So far, many attempts have been made to determine the critical strain, which is described by three widely used methods in this study. Also, for determining the squeezing potential in all studies, the squeezing amount is 1%. Given that the results obtained from different methods for determining the critical strain, using different parameters and different results, In this study, AI has been tried to fine-tune the results. For this purpose, the intelligent learning machine algorithm will be used in the Rapidminer data mining software. In the present study, by gathering information from various tunnels in valid articles, the conditions are defined as three stable, semi-stable, and unstable states. Outputs the learning machine includes the relationship of parameters based on the conditions in the tunnel, the effect of each of the parameters on the other according to the tunnel conditions.

Keywords

References

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